Leverage the power of SQL to perform geospatial analysis and increase your speed and efficiency working with a variety of spatial applications such as PostGIS and QGIS
Geospatial analysis is used in almost every industry to answer location-related questions. Combined with the power of SQL, which is becoming a popular choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems easily. This book shows you how to detect and quantify patterns in datasets through data exploration, data visualization, data engineering, and the application of analysis and spatial techniques.
You'll begin by exploring the fundamentals of geospatial analysis and understand its importance along with vector and raster models, among other things. You'll then look at the framework for geospatial analysis using SQL and progress through the chapters to create a spatial database and analyze it. In the next part, you'll advance to learning about using SQL functions and building SQL queries.
By the end of this book, you'll be able to make the most of open source libraries and frameworks such as PostGIS and QGIS for analyzing spatial information.
This book is for anyone looking to leverage their SQL knowledge to perform geospatial analysis. GIS analysts, data analysts, and data scientists with a basic understanding of both geospatial analysis and SQL will find this book useful.
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Bonny applies advanced data analytics including data engineering and geoenrichment to discussions of poverty, race, and gender. Core themes of racism, class exploitation, sexism and nationalism and heterosexism all contribute to social inequality. Bonny redefines how we measure these attributes and how we can more accurately identify factors amenable to intervention. Spatial data hosts a variety of physical and cultural features to reveal distribution patterns helping analysts and data professionals understand underlying drivers of these patterns.Bonny is a popular conference keynote and workshop leader. Professional goals include exploring large datasets and curating empathetic answers to larger questions--making a big world seem smaller.
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